Overview

Dataset statistics

Number of variables12
Number of observations1000
Missing cells192
Missing cells (%)1.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory93.9 KiB
Average record size in memory96.1 B

Variable types

Numeric7
Text5

Alerts

Metascore is highly overall correlated with RatingHigh correlation
Rating is highly overall correlated with Metascore and 1 other fieldsHigh correlation
Revenue (Millions) is highly overall correlated with VotesHigh correlation
Votes is highly overall correlated with Rating and 2 other fieldsHigh correlation
Year is highly overall correlated with VotesHigh correlation
Revenue (Millions) has 128 (12.8%) missing valuesMissing
Metascore has 64 (6.4%) missing valuesMissing
Rank is uniformly distributedUniform
Rank has unique valuesUnique
Description has unique valuesUnique

Reproduction

Analysis started2025-12-07 03:47:29.190735
Analysis finished2025-12-07 03:48:11.020494
Duration41.83 seconds
Software versionydata-profiling vv4.18.0
Download configurationconfig.json

Variables

Rank
Real number (ℝ)

Uniform  Unique 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean500.5
Minimum1
Maximum1000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2025-12-07T09:18:11.722907image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile50.95
Q1250.75
median500.5
Q3750.25
95-th percentile950.05
Maximum1000
Range999
Interquartile range (IQR)499.5

Descriptive statistics

Standard deviation288.81944
Coefficient of variation (CV)0.57706181
Kurtosis-1.2
Mean500.5
Median Absolute Deviation (MAD)250
Skewness0
Sum500500
Variance83416.667
MonotonicityStrictly increasing
2025-12-07T09:18:13.051520image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11
 
0.1%
6721
 
0.1%
6591
 
0.1%
6601
 
0.1%
6611
 
0.1%
6621
 
0.1%
6631
 
0.1%
6641
 
0.1%
6651
 
0.1%
6661
 
0.1%
Other values (990)990
99.0%
ValueCountFrequency (%)
11
0.1%
21
0.1%
31
0.1%
41
0.1%
51
0.1%
61
0.1%
71
0.1%
81
0.1%
91
0.1%
101
0.1%
ValueCountFrequency (%)
10001
0.1%
9991
0.1%
9981
0.1%
9971
0.1%
9961
0.1%
9951
0.1%
9941
0.1%
9931
0.1%
9921
0.1%
9911
0.1%

Title
Text

Distinct999
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2025-12-07T09:18:15.327009image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length61
Median length44
Mean length14.539
Min length2

Characters and Unicode

Total characters14539
Distinct characters81
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique998 ?
Unique (%)99.8%

Sample

1st rowGuardians of the Galaxy
2nd rowPrometheus
3rd rowSplit
4th rowSing
5th rowSuicide Squad
ValueCountFrequency (%)
the305
 
11.7%
of92
 
3.5%
a29
 
1.1%
in22
 
0.8%
and22
 
0.8%
222
 
0.8%
15
 
0.6%
man12
 
0.5%
to12
 
0.5%
i11
 
0.4%
Other values (1429)2063
79.2%
2025-12-07T09:18:18.603640image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1605
 
11.0%
e1507
 
10.4%
a884
 
6.1%
o851
 
5.9%
n828
 
5.7%
r799
 
5.5%
i775
 
5.3%
t720
 
5.0%
s609
 
4.2%
h539
 
3.7%
Other values (71)5422
37.3%

Most occurring categories

ValueCountFrequency (%)
(unknown)14539
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1605
 
11.0%
e1507
 
10.4%
a884
 
6.1%
o851
 
5.9%
n828
 
5.7%
r799
 
5.5%
i775
 
5.3%
t720
 
5.0%
s609
 
4.2%
h539
 
3.7%
Other values (71)5422
37.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown)14539
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1605
 
11.0%
e1507
 
10.4%
a884
 
6.1%
o851
 
5.9%
n828
 
5.7%
r799
 
5.5%
i775
 
5.3%
t720
 
5.0%
s609
 
4.2%
h539
 
3.7%
Other values (71)5422
37.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown)14539
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1605
 
11.0%
e1507
 
10.4%
a884
 
6.1%
o851
 
5.9%
n828
 
5.7%
r799
 
5.5%
i775
 
5.3%
t720
 
5.0%
s609
 
4.2%
h539
 
3.7%
Other values (71)5422
37.3%

Genre
Text

Distinct207
Distinct (%)20.7%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2025-12-07T09:18:20.304751image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length26
Median length21
Mean length18.095
Min length5

Characters and Unicode

Total characters18095
Distinct characters31
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique85 ?
Unique (%)8.5%

Sample

1st rowAction,Adventure,Sci-Fi
2nd rowAdventure,Mystery,Sci-Fi
3rd rowHorror,Thriller
4th rowAnimation,Comedy,Family
5th rowAction,Adventure,Fantasy
ValueCountFrequency (%)
action,adventure,sci-fi50
 
5.0%
drama48
 
4.8%
comedy,drama,romance35
 
3.5%
comedy32
 
3.2%
drama,romance31
 
3.1%
animation,adventure,comedy27
 
2.7%
action,adventure,fantasy27
 
2.7%
comedy,drama27
 
2.7%
comedy,romance26
 
2.6%
crime,drama,thriller24
 
2.4%
Other values (197)673
67.3%
2025-12-07T09:18:23.056280image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r1923
 
10.6%
a1568
 
8.7%
,1555
 
8.6%
e1403
 
7.8%
m1183
 
6.5%
i1168
 
6.5%
o1138
 
6.3%
n909
 
5.0%
t872
 
4.8%
y753
 
4.2%
Other values (21)5623
31.1%

Most occurring categories

ValueCountFrequency (%)
(unknown)18095
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r1923
 
10.6%
a1568
 
8.7%
,1555
 
8.6%
e1403
 
7.8%
m1183
 
6.5%
i1168
 
6.5%
o1138
 
6.3%
n909
 
5.0%
t872
 
4.8%
y753
 
4.2%
Other values (21)5623
31.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown)18095
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r1923
 
10.6%
a1568
 
8.7%
,1555
 
8.6%
e1403
 
7.8%
m1183
 
6.5%
i1168
 
6.5%
o1138
 
6.3%
n909
 
5.0%
t872
 
4.8%
y753
 
4.2%
Other values (21)5623
31.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown)18095
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r1923
 
10.6%
a1568
 
8.7%
,1555
 
8.6%
e1403
 
7.8%
m1183
 
6.5%
i1168
 
6.5%
o1138
 
6.3%
n909
 
5.0%
t872
 
4.8%
y753
 
4.2%
Other values (21)5623
31.1%

Description
Text

Unique 

Distinct1000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2025-12-07T09:18:24.813161image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length421
Median length212
Mean length163.232
Min length42

Characters and Unicode

Total characters163232
Distinct characters82
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1000 ?
Unique (%)100.0%

Sample

1st rowA group of intergalactic criminals are forced to work together to stop a fanatical warrior from taking control of the universe.
2nd rowFollowing clues to the origin of mankind, a team finds a structure on a distant moon, but they soon realize they are not alone.
3rd rowThree girls are kidnapped by a man with a diagnosed 23 distinct personalities. They must try to escape before the apparent emergence of a frightful new 24th.
4th rowIn a city of humanoid animals, a hustling theater impresario's attempt to save his theater with a singing competition becomes grander than he anticipates even as its finalists' find that their lives will never be the same.
5th rowA secret government agency recruits some of the most dangerous incarcerated super-villains to form a defensive task force. Their first mission: save the world from the apocalypse.
ValueCountFrequency (%)
a1626
 
5.8%
the1360
 
4.9%
to934
 
3.3%
of807
 
2.9%
and716
 
2.6%
in578
 
2.1%
his487
 
1.7%
an304
 
1.1%
is296
 
1.1%
with274
 
1.0%
Other values (6172)20539
73.6%
2025-12-07T09:18:27.856163image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
26921
16.5%
e15840
 
9.7%
t10926
 
6.7%
a10686
 
6.5%
i9657
 
5.9%
o9618
 
5.9%
n9602
 
5.9%
r9227
 
5.7%
s8727
 
5.3%
h6513
 
4.0%
Other values (72)45515
27.9%

Most occurring categories

ValueCountFrequency (%)
(unknown)163232
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
26921
16.5%
e15840
 
9.7%
t10926
 
6.7%
a10686
 
6.5%
i9657
 
5.9%
o9618
 
5.9%
n9602
 
5.9%
r9227
 
5.7%
s8727
 
5.3%
h6513
 
4.0%
Other values (72)45515
27.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown)163232
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
26921
16.5%
e15840
 
9.7%
t10926
 
6.7%
a10686
 
6.5%
i9657
 
5.9%
o9618
 
5.9%
n9602
 
5.9%
r9227
 
5.7%
s8727
 
5.3%
h6513
 
4.0%
Other values (72)45515
27.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown)163232
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
26921
16.5%
e15840
 
9.7%
t10926
 
6.7%
a10686
 
6.5%
i9657
 
5.9%
o9618
 
5.9%
n9602
 
5.9%
r9227
 
5.7%
s8727
 
5.3%
h6513
 
4.0%
Other values (72)45515
27.9%
Distinct644
Distinct (%)64.4%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2025-12-07T09:18:30.075389image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length32
Median length21
Mean length13.139
Min length3

Characters and Unicode

Total characters13139
Distinct characters69
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique444 ?
Unique (%)44.4%

Sample

1st rowJames Gunn
2nd rowRidley Scott
3rd rowM. Night Shyamalan
4th rowChristophe Lourdelet
5th rowDavid Ayer
ValueCountFrequency (%)
david38
 
1.8%
john25
 
1.2%
michael22
 
1.1%
james21
 
1.0%
scott20
 
1.0%
paul19
 
0.9%
robert14
 
0.7%
steven13
 
0.6%
lee12
 
0.6%
peter12
 
0.6%
Other values (977)1896
90.6%
2025-12-07T09:18:32.662640image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e1223
 
9.3%
1092
 
8.3%
a1056
 
8.0%
n937
 
7.1%
r875
 
6.7%
o783
 
6.0%
i740
 
5.6%
l604
 
4.6%
t486
 
3.7%
s467
 
3.6%
Other values (59)4876
37.1%

Most occurring categories

ValueCountFrequency (%)
(unknown)13139
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e1223
 
9.3%
1092
 
8.3%
a1056
 
8.0%
n937
 
7.1%
r875
 
6.7%
o783
 
6.0%
i740
 
5.6%
l604
 
4.6%
t486
 
3.7%
s467
 
3.6%
Other values (59)4876
37.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown)13139
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e1223
 
9.3%
1092
 
8.3%
a1056
 
8.0%
n937
 
7.1%
r875
 
6.7%
o783
 
6.0%
i740
 
5.6%
l604
 
4.6%
t486
 
3.7%
s467
 
3.6%
Other values (59)4876
37.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown)13139
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e1223
 
9.3%
1092
 
8.3%
a1056
 
8.0%
n937
 
7.1%
r875
 
6.7%
o783
 
6.0%
i740
 
5.6%
l604
 
4.6%
t486
 
3.7%
s467
 
3.6%
Other values (59)4876
37.1%

Actors
Text

Distinct996
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size7.9 KiB
2025-12-07T09:18:33.681012image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length77
Median length70
Mean length58.288
Min length43

Characters and Unicode

Total characters58288
Distinct characters79
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique992 ?
Unique (%)99.2%

Sample

1st rowChris Pratt, Vin Diesel, Bradley Cooper, Zoe Saldana
2nd rowNoomi Rapace, Logan Marshall-Green, Michael Fassbender, Charlize Theron
3rd rowJames McAvoy, Anya Taylor-Joy, Haley Lu Richardson, Jessica Sula
4th rowMatthew McConaughey,Reese Witherspoon, Seth MacFarlane, Scarlett Johansson
5th rowWill Smith, Jared Leto, Margot Robbie, Viola Davis
ValueCountFrequency (%)
michael62
 
0.8%
james50
 
0.6%
tom44
 
0.6%
john42
 
0.5%
chris42
 
0.5%
jason41
 
0.5%
robert37
 
0.5%
jennifer35
 
0.4%
mark35
 
0.4%
ben31
 
0.4%
Other values (2924)7441
94.7%
2025-12-07T09:18:36.193936image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6860
 
11.8%
e5007
 
8.6%
a4812
 
8.3%
n3867
 
6.6%
i3216
 
5.5%
r3171
 
5.4%
,2999
 
5.1%
o2949
 
5.1%
l2811
 
4.8%
s1931
 
3.3%
Other values (69)20665
35.5%

Most occurring categories

ValueCountFrequency (%)
(unknown)58288
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
6860
 
11.8%
e5007
 
8.6%
a4812
 
8.3%
n3867
 
6.6%
i3216
 
5.5%
r3171
 
5.4%
,2999
 
5.1%
o2949
 
5.1%
l2811
 
4.8%
s1931
 
3.3%
Other values (69)20665
35.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown)58288
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
6860
 
11.8%
e5007
 
8.6%
a4812
 
8.3%
n3867
 
6.6%
i3216
 
5.5%
r3171
 
5.4%
,2999
 
5.1%
o2949
 
5.1%
l2811
 
4.8%
s1931
 
3.3%
Other values (69)20665
35.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown)58288
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
6860
 
11.8%
e5007
 
8.6%
a4812
 
8.3%
n3867
 
6.6%
i3216
 
5.5%
r3171
 
5.4%
,2999
 
5.1%
o2949
 
5.1%
l2811
 
4.8%
s1931
 
3.3%
Other values (69)20665
35.5%

Year
Real number (ℝ)

High correlation 

Distinct11
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2012.783
Minimum2006
Maximum2016
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2025-12-07T09:18:36.739123image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum2006
5-th percentile2007
Q12010
median2014
Q32016
95-th percentile2016
Maximum2016
Range10
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.2059615
Coefficient of variation (CV)0.0015928004
Kurtosis-0.82196398
Mean2012.783
Median Absolute Deviation (MAD)2
Skewness-0.68987871
Sum2012783
Variance10.278189
MonotonicityNot monotonic
2025-12-07T09:18:37.453726image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
2016297
29.7%
2015127
12.7%
201498
 
9.8%
201391
 
9.1%
201264
 
6.4%
201163
 
6.3%
201060
 
6.0%
200753
 
5.3%
200852
 
5.2%
200951
 
5.1%
ValueCountFrequency (%)
200644
 
4.4%
200753
5.3%
200852
5.2%
200951
5.1%
201060
6.0%
201163
6.3%
201264
6.4%
201391
9.1%
201498
9.8%
2015127
12.7%
ValueCountFrequency (%)
2016297
29.7%
2015127
12.7%
201498
 
9.8%
201391
 
9.1%
201264
 
6.4%
201163
 
6.3%
201060
 
6.0%
200951
 
5.1%
200852
 
5.2%
200753
 
5.3%

Runtime (Minutes)
Real number (ℝ)

Distinct94
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean113.172
Minimum66
Maximum191
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2025-12-07T09:18:38.354600image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum66
5-th percentile88
Q1100
median111
Q3123
95-th percentile150
Maximum191
Range125
Interquartile range (IQR)23

Descriptive statistics

Standard deviation18.810908
Coefficient of variation (CV)0.16621521
Kurtosis0.8583211
Mean113.172
Median Absolute Deviation (MAD)12
Skewness0.84671273
Sum113172
Variance353.85027
MonotonicityNot monotonic
2025-12-07T09:18:39.276945image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10831
 
3.1%
10028
 
2.8%
11727
 
2.7%
11826
 
2.6%
10626
 
2.6%
11026
 
2.6%
10225
 
2.5%
11224
 
2.4%
12323
 
2.3%
10423
 
2.3%
Other values (84)741
74.1%
ValueCountFrequency (%)
661
 
0.1%
732
 
0.2%
802
 
0.2%
815
0.5%
821
 
0.1%
836
0.6%
843
 
0.3%
859
0.9%
868
0.8%
879
0.9%
ValueCountFrequency (%)
1911
 
0.1%
1871
 
0.1%
1803
0.3%
1721
 
0.1%
1701
 
0.1%
1693
0.3%
1661
 
0.1%
1655
0.5%
1641
 
0.1%
1631
 
0.1%

Rating
Real number (ℝ)

High correlation 

Distinct55
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.7232
Minimum1.9
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2025-12-07T09:18:40.132515image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1.9
5-th percentile5.1
Q16.2
median6.8
Q37.4
95-th percentile8.1
Maximum9
Range7.1
Interquartile range (IQR)1.2

Descriptive statistics

Standard deviation0.94542879
Coefficient of variation (CV)0.14062185
Kurtosis1.3222703
Mean6.7232
Median Absolute Deviation (MAD)0.6
Skewness-0.74314194
Sum6723.2
Variance0.8938356
MonotonicityNot monotonic
2025-12-07T09:18:41.042574image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.152
 
5.2%
6.748
 
4.8%
746
 
4.6%
6.344
 
4.4%
7.342
 
4.2%
7.242
 
4.2%
6.642
 
4.2%
6.540
 
4.0%
7.840
 
4.0%
6.237
 
3.7%
Other values (45)567
56.7%
ValueCountFrequency (%)
1.91
 
0.1%
2.72
0.2%
3.21
 
0.1%
3.52
0.2%
3.72
0.2%
3.93
0.3%
41
 
0.1%
4.11
 
0.1%
4.22
0.2%
4.34
0.4%
ValueCountFrequency (%)
91
 
0.1%
8.82
 
0.2%
8.63
 
0.3%
8.56
 
0.6%
8.44
 
0.4%
8.37
 
0.7%
8.210
 
1.0%
8.126
2.6%
819
1.9%
7.923
2.3%

Votes
Real number (ℝ)

High correlation 

Distinct997
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean169808.26
Minimum61
Maximum1791916
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2025-12-07T09:18:41.921628image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum61
5-th percentile1260.35
Q136309
median110799
Q3239909.75
95-th percentile526551.85
Maximum1791916
Range1791855
Interquartile range (IQR)203600.75

Descriptive statistics

Standard deviation188762.65
Coefficient of variation (CV)1.1116223
Kurtosis11.312681
Mean169808.26
Median Absolute Deviation (MAD)88402
Skewness2.5079185
Sum1.6980826 × 108
Variance3.5631337 × 1010
MonotonicityNot monotonic
2025-12-07T09:18:42.987640image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
971412
 
0.2%
2912
 
0.2%
14272
 
0.2%
7570741
 
0.1%
57961
 
0.1%
1688751
 
0.1%
1363231
 
0.1%
263201
 
0.1%
752911
 
0.1%
2067071
 
0.1%
Other values (987)987
98.7%
ValueCountFrequency (%)
611
0.1%
961
0.1%
1021
0.1%
1151
0.1%
1641
0.1%
1731
0.1%
1781
0.1%
1981
0.1%
2021
0.1%
2201
0.1%
ValueCountFrequency (%)
17919161
0.1%
15836251
0.1%
12226451
0.1%
10477471
0.1%
10455881
0.1%
10391151
0.1%
9590651
0.1%
9374141
0.1%
9354081
0.1%
9131521
0.1%

Revenue (Millions)
Real number (ℝ)

High correlation  Missing 

Distinct814
Distinct (%)93.3%
Missing128
Missing (%)12.8%
Infinite0
Infinite (%)0.0%
Mean82.956376
Minimum0
Maximum936.63
Zeros1
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2025-12-07T09:18:44.194575image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.211
Q113.27
median47.985
Q3113.715
95-th percentile293.88
Maximum936.63
Range936.63
Interquartile range (IQR)100.445

Descriptive statistics

Standard deviation103.25354
Coefficient of variation (CV)1.2446727
Kurtosis10.607635
Mean82.956376
Median Absolute Deviation (MAD)41.285
Skewness2.5925159
Sum72337.96
Variance10661.294
MonotonicityNot monotonic
2025-12-07T09:18:45.135542image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.037
 
0.7%
0.015
 
0.5%
0.024
 
0.4%
0.044
 
0.4%
0.054
 
0.4%
0.324
 
0.4%
0.543
 
0.3%
2.23
 
0.3%
1.293
 
0.3%
0.153
 
0.3%
Other values (804)832
83.2%
(Missing)128
 
12.8%
ValueCountFrequency (%)
01
 
0.1%
0.015
0.5%
0.024
0.4%
0.037
0.7%
0.044
0.4%
0.054
0.4%
0.062
 
0.2%
0.072
 
0.2%
0.081
 
0.1%
0.092
 
0.2%
ValueCountFrequency (%)
936.631
0.1%
760.511
0.1%
652.181
0.1%
623.281
0.1%
533.321
0.1%
532.171
0.1%
486.291
0.1%
458.991
0.1%
448.131
0.1%
424.651
0.1%

Metascore
Real number (ℝ)

High correlation  Missing 

Distinct84
Distinct (%)9.0%
Missing64
Missing (%)6.4%
Infinite0
Infinite (%)0.0%
Mean58.985043
Minimum11
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 KiB
2025-12-07T09:18:46.012282image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile31
Q147
median59.5
Q372
95-th percentile85
Maximum100
Range89
Interquartile range (IQR)25

Descriptive statistics

Standard deviation17.194757
Coefficient of variation (CV)0.29151046
Kurtosis-0.61220515
Mean58.985043
Median Absolute Deviation (MAD)12.5
Skewness-0.12388735
Sum55210
Variance295.65967
MonotonicityNot monotonic
2025-12-07T09:18:46.955923image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6625
 
2.5%
6825
 
2.5%
7225
 
2.5%
6424
 
2.4%
5723
 
2.3%
6522
 
2.2%
5122
 
2.2%
7621
 
2.1%
8121
 
2.1%
4821
 
2.1%
Other values (74)707
70.7%
(Missing)64
 
6.4%
ValueCountFrequency (%)
111
 
0.1%
151
 
0.1%
161
 
0.1%
184
0.4%
191
 
0.1%
201
 
0.1%
223
0.3%
236
0.6%
242
 
0.2%
252
 
0.2%
ValueCountFrequency (%)
1001
 
0.1%
991
 
0.1%
981
 
0.1%
964
0.4%
953
0.3%
943
0.3%
933
0.3%
922
 
0.2%
911
 
0.1%
905
0.5%

Interactions

2025-12-07T09:18:03.382197image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:31.526899image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:36.960964image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:42.072504image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:47.712247image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:52.730076image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:58.525545image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:18:04.072867image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:32.345120image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:37.711322image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:42.840617image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:48.502223image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:53.522479image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:59.182678image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:18:04.785065image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:33.323956image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:38.449794image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:43.821505image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:49.198367image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:54.485694image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:59.890213image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:18:05.664579image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:34.068859image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:39.202336image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:44.590820image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:49.827930image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:55.350788image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:18:00.632864image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:18:06.400136image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:34.800965image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:39.958658image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:45.343960image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:50.498293image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:56.158183image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:18:01.350509image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:18:07.145387image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:35.614537image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:40.737740image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:46.180063image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:51.320000image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:56.968915image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:18:02.073283image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:18:07.815647image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:36.307393image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:41.419028image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:46.931607image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:52.038901image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:17:57.731113image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-07T09:18:02.712215image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-12-07T09:18:47.623451image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
MetascoreRankRatingRevenue (Millions)Runtime (Minutes)VotesYear
Metascore1.000-0.1930.6650.0540.1990.276-0.063
Rank-0.1931.000-0.229-0.233-0.224-0.202-0.290
Rating0.665-0.2291.0000.1590.3830.520-0.228
Revenue (Millions)0.054-0.2330.1591.0000.2470.701-0.239
Runtime (Minutes)0.199-0.2240.3830.2471.0000.408-0.174
Votes0.276-0.2020.5200.7010.4081.000-0.610
Year-0.063-0.290-0.228-0.239-0.174-0.6101.000

Missing values

2025-12-07T09:18:08.866122image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-12-07T09:18:09.673860image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2025-12-07T09:18:10.611845image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

RankTitleGenreDescriptionDirectorActorsYearRuntime (Minutes)RatingVotesRevenue (Millions)Metascore
01Guardians of the GalaxyAction,Adventure,Sci-FiA group of intergalactic criminals are forced to work together to stop a fanatical warrior from taking control of the universe.James GunnChris Pratt, Vin Diesel, Bradley Cooper, Zoe Saldana20141218.1757074333.1376.0
12PrometheusAdventure,Mystery,Sci-FiFollowing clues to the origin of mankind, a team finds a structure on a distant moon, but they soon realize they are not alone.Ridley ScottNoomi Rapace, Logan Marshall-Green, Michael Fassbender, Charlize Theron20121247.0485820126.4665.0
23SplitHorror,ThrillerThree girls are kidnapped by a man with a diagnosed 23 distinct personalities. They must try to escape before the apparent emergence of a frightful new 24th.M. Night ShyamalanJames McAvoy, Anya Taylor-Joy, Haley Lu Richardson, Jessica Sula20161177.3157606138.1262.0
34SingAnimation,Comedy,FamilyIn a city of humanoid animals, a hustling theater impresario's attempt to save his theater with a singing competition becomes grander than he anticipates even as its finalists' find that their lives will never be the same.Christophe LourdeletMatthew McConaughey,Reese Witherspoon, Seth MacFarlane, Scarlett Johansson20161087.260545270.3259.0
45Suicide SquadAction,Adventure,FantasyA secret government agency recruits some of the most dangerous incarcerated super-villains to form a defensive task force. Their first mission: save the world from the apocalypse.David AyerWill Smith, Jared Leto, Margot Robbie, Viola Davis20161236.2393727325.0240.0
56The Great WallAction,Adventure,FantasyEuropean mercenaries searching for black powder become embroiled in the defense of the Great Wall of China against a horde of monstrous creatures.Yimou ZhangMatt Damon, Tian Jing, Willem Dafoe, Andy Lau20161036.15603645.1342.0
67La La LandComedy,Drama,MusicA jazz pianist falls for an aspiring actress in Los Angeles.Damien ChazelleRyan Gosling, Emma Stone, Rosemarie DeWitt, J.K. Simmons20161288.3258682151.0693.0
78MindhornComedyA has-been actor best known for playing the title character in the 1980s detective series "Mindhorn" must work with the police when a serial killer says that he will only speak with Detective Mindhorn, whom he believes to be a real person.Sean FoleyEssie Davis, Andrea Riseborough, Julian Barratt,Kenneth Branagh2016896.42490NaN71.0
89The Lost City of ZAction,Adventure,BiographyA true-life drama, centering on British explorer Col. Percival Fawcett, who disappeared while searching for a mysterious city in the Amazon in the 1920s.James GrayCharlie Hunnam, Robert Pattinson, Sienna Miller, Tom Holland20161417.171888.0178.0
910PassengersAdventure,Drama,RomanceA spacecraft traveling to a distant colony planet and transporting thousands of people has a malfunction in its sleep chambers. As a result, two passengers are awakened 90 years early.Morten TyldumJennifer Lawrence, Chris Pratt, Michael Sheen,Laurence Fishburne20161167.0192177100.0141.0
RankTitleGenreDescriptionDirectorActorsYearRuntime (Minutes)RatingVotesRevenue (Millions)Metascore
990991Underworld: Rise of the LycansAction,Adventure,FantasyAn origins story centered on the centuries-old feud between the race of aristocratic vampires and their onetime slaves, the Lycans.Patrick TatopoulosRhona Mitra, Michael Sheen, Bill Nighy, Steven Mackintosh2009926.612970845.8044.0
991992Taare Zameen ParDrama,Family,MusicAn eight-year-old boy is thought to be a lazy trouble-maker, until the new art teacher has the patience and compassion to discover the real problem behind his struggles in school.Aamir KhanDarsheel Safary, Aamir Khan, Tanay Chheda, Sachet Engineer20071658.51026971.2042.0
992993Take Me Home TonightComedy,Drama,RomanceFour years after graduation, an awkward high school genius uses his sister's boyfriend's Labor Day party as the perfect opportunity to make his move on his high school crush.Michael DowseTopher Grace, Anna Faris, Dan Fogler, Teresa Palmer2011976.3454196.92NaN
993994Resident Evil: AfterlifeAction,Adventure,HorrorWhile still out to destroy the evil Umbrella Corporation, Alice joins a group of survivors living in a prison surrounded by the infected who also want to relocate to the mysterious but supposedly unharmed safe haven known only as Arcadia.Paul W.S. AndersonMilla Jovovich, Ali Larter, Wentworth Miller,Kim Coates2010975.914090060.1337.0
994995Project XComedy3 high school seniors throw a birthday party to make a name for themselves. As the night progresses, things spiral out of control as word of the party spreads.Nima NourizadehThomas Mann, Oliver Cooper, Jonathan Daniel Brown, Dax Flame2012886.716408854.7248.0
995996Secret in Their EyesCrime,Drama,MysteryA tight-knit team of rising investigators, along with their supervisor, is suddenly torn apart when they discover that one of their own teenage daughters has been brutally murdered.Billy RayChiwetel Ejiofor, Nicole Kidman, Julia Roberts, Dean Norris20151116.227585NaN45.0
996997Hostel: Part IIHorrorThree American college students studying abroad are lured to a Slovakian hostel, and discover the grim reality behind it.Eli RothLauren German, Heather Matarazzo, Bijou Phillips, Roger Bart2007945.57315217.5446.0
997998Step Up 2: The StreetsDrama,Music,RomanceRomantic sparks occur between two dance students from different backgrounds at the Maryland School of the Arts.Jon M. ChuRobert Hoffman, Briana Evigan, Cassie Ventura, Adam G. Sevani2008986.27069958.0150.0
998999Search PartyAdventure,ComedyA pair of friends embark on a mission to reunite their pal with the woman he was going to marry.Scot ArmstrongAdam Pally, T.J. Miller, Thomas Middleditch,Shannon Woodward2014935.64881NaN22.0
9991000Nine LivesComedy,Family,FantasyA stuffy businessman finds himself trapped inside the body of his family's cat.Barry SonnenfeldKevin Spacey, Jennifer Garner, Robbie Amell,Cheryl Hines2016875.31243519.6411.0